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JOURNAL OF INTELLIGENT SYSTEMS WITH APPLICATIONS
J. Intell. Syst. Appl.
E-ISSN: 2667-6893

Detecting Abnormalities in Heart Sounds

Kalp Seslerindeki Anormalliklerin Belirlenmesi

How to cite: Telçeken M, Kutlu Y. Detecting abnormalities in heart sounds. J Intell Syst Appl 2021; 4(2): 137-143. DOI: 10.54856/jiswa.202112180

Full Text: PDF, in Turkish.

Total number of downloads: 134

Title: Detecting Abnormalities in Heart Sounds

Abstract: Heart sounds are important data that reflect the state of the heart. It is possible to prevent larger problems that may occur with early diagnosis of abnormalities in heart sounds. Therefore, in this study, the detection of abnormalities in heart sounds has been studied. In order to detect abnormalities in heart sounds, the heartbeat-sounds data set obtained free of charge from the kaggle.com website was examined. Mel frequency cepstral coefficients (MFCCs) were used in the selection of the characteristics of the sounds. Parameters such as the number of filters to be applied for MFCCs, the number of attributes to be extracted are examined separately with different values. The classification performance of heart sounds with feature matrices extracted in different parameters of MFCCs with K-nearest neighbor algorithm was investigated. The classification performance of different feature extractions was compared and the best case was tried to be determined. Two different records that make up the data set were examined separately as normal and abnormal. Then, the new data set obtained by combining the two records was examined as normal and abnormal.

Keywords: MFCC; k-nearest negihbors; heart sound; classification


Başlık: Kalp Seslerindeki Anormalliklerin Belirlenmesi

Özet: Kalp sesleri kalbin durumunu yansıtan önemli verilerdir. Kalp seslerindeki anormalliklerin erken teşhisi ile oluşabilecek daha büyük sorunları önlemek mümkün olabilmektedir. Bu nedenle bu çalışmada kalp seslerindeki anormalliklerin tespiti üzerine çalışılmıştır. Kalp seslerindeki anormallikleri tespit etmek için kaggle.com internet sitesi üzerinden ücretsiz olarak elde edilmiş kalp hızı - sesleri veri seti incelenmiştir. Seslerin özelliklerinin seçiminde Mel frekansı sepstral katsayıları (MFCCs) kullanılmıştır. MFCCs için uygulanacak filtre sayısı, çıkarılacak öznitelik sayısı gibi parametreler farklı değerlerde ayrı ayrı incelenmiştir. Kalp seslerinin MFCCs’nin farklı parametrelerinden çıkartılan öznitelik matrisleri K-en yakın komşu algoritması ile sınıflandırma başarımları incelenmiştir. Farklı öznitelik çıkarımlarının sınıflandırma başarımları karşılaştırılmış ve en iyi durum tespit edilmeye çalışılmıştır. Veri setini oluşturan iki farklı kayıt ayrı ayrı normal ve anormal olarak incelenmiştir. Sonrada iki kayıt birleştirilerek elde edilen yeni veri seti normal ve anormal olarak incelenmiştir.

Anahtar kelimeler: MFCCs; k-yakın komşu; kalp sesi; sınıflandırma


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